AI agents for
real estate teams.
Qualify leads in 2 minutes, match buyers to listings in real time, schedule showings without the back-and-forth, and generate CMAs in minutes — with Fair Housing compliance built into the architecture.
Where real estate AI agents close the gap.
Four workflows where we consistently see measurable impact within the first 90 days of deployment.
Lead Qualification & Scoring
Before
Internet leads hit the CRM and agents call them back hours later — if they call at all. 70% of leads never get a first response within 30 minutes. Agents spend half their day calling people who are 6 months away from buying.
After
An AI agent responds to every new lead within 2 minutes — via text, email, or web chat — qualifies them through natural conversation, scores them based on timeline, budget, and pre-approval status, and routes hot leads directly to the right agent's phone with full context.
2-min avg response time
Property Matching Agent
Before
Agents manually search MLS based on what the buyer said last week. They miss new listings that match. Buyers get frustrated waiting for updates. The agent who sends the best listing first wins the deal — and your agents are slow.
After
A property matching agent monitors MLS feeds in real time, matches new and updated listings against each buyer's criteria and behavior patterns, and sends personalized property alerts with context — why this listing matches, comparable sales data, and a one-tap showing request.
Real-time listing match alerts
Automated Showing Scheduling
Before
Scheduling a showing involves 5–10 back-and-forth texts between buyer, listing agent, and showing service. Agents spend 30 minutes per showing on logistics. Weekend showing routes are inefficient because nobody optimizes the sequence.
After
The AI agent handles showing requests end-to-end — checking listing availability, proposing time slots that optimize the buyer's route, confirming with listing agents or showing services, and sending the buyer a mapped itinerary. Rescheduling happens via a single text reply.
80% less scheduling overhead
Market Analysis & CMA Automation
Before
Pulling a CMA takes 45–60 minutes: searching comps, adjusting for differences, formatting the report, and presenting it to the seller. Agents avoid pulling CMAs for anything other than listing appointments, missing nurture opportunities.
After
An AI agent generates draft CMAs in minutes by pulling comparable sales from MLS, adjusting for square footage, condition, lot size, and market trends, and producing a formatted report. The agent reviews and adjusts before presenting — cutting CMA prep from 60 minutes to 10.
85% faster CMA preparation
Built for leaders who need scale without more headcount.
Managing brokers with high internet lead volume
You're paying for Zillow, Realtor.com, and Google Ads leads — but your agents can't respond fast enough. An AI qualification agent ensures every lead gets a response in under 2 minutes, 24/7, so you stop paying for leads that go to waste.
VP of Sales optimizing agent productivity
Your top producers are spending hours on admin tasks instead of face-to-face selling. AI agents handle lead qualification, showing scheduling, and CMA prep so your human agents spend their time on the high-value activities that close deals.
Marketing directors measuring lead source ROI
AI qualification agents capture structured data on every lead interaction — timeline, budget, motivation, and objections — giving you lead quality metrics by source that go far beyond the raw lead count your portals report.
CTOs building the next-generation brokerage stack
You see the industry moving toward AI-assisted sales and want to position your brokerage as a technology leader. We build AI agents that integrate with your existing CRM and MLS infrastructure without replacing what already works.
From lead flow analysis to production agent.
Lead Flow Analysis
We map your lead sources, response times, qualification criteria, and conversion funnel. We analyze 6–12 months of CRM data to identify which lead signals predict conversion and where the biggest time sinks are in your agents' daily workflow.
Agent Architecture & MLS Integration
We design the AI agent architecture — conversation flows, scoring models, MLS data access, CRM integration, and Fair Housing compliance guardrails. Everything is documented and reviewed with your team before development starts.
Pilot with Selected Teams
We deploy to a controlled group — one team or one lead source — and measure response time, qualification accuracy, agent satisfaction, and conversion rate impact before expanding brokerage-wide.
Scale & Optimize
Based on pilot results, we expand to all teams and lead sources, fine-tune scoring models based on real conversion data, add new capabilities (showing scheduling, CMA automation), and build monitoring dashboards for ongoing performance tracking.
Questions about real estate AI agents.
How accurate is AI lead qualification for real estate?
AI lead qualification accuracy depends on two factors: the quality of your historical data and the signals the agent has access to. With 6–12 months of CRM data showing which leads converted and which didn't, we can build scoring models that identify your top 20% leads with 75–85% accuracy. The agent scores leads based on behavioral signals — property search frequency, price range consistency, response speed, pre-approval status, and timeline language in conversations. The key insight: AI qualification doesn't replace human judgment on your best leads. It filters out the 60–70% of leads that are months away from buying so your agents can focus on the 30% who are ready now.
How does the AI agent access MLS data?
The AI agent connects to your MLS through the RESO Web API (or RETS where the local MLS hasn't migrated yet) and syncs listing data into a structured database that the agent can query in real time. This gives the property matching agent access to active listings, price history, days on market, status changes, and property details. For CMAs, the agent pulls comparable sales data from the same feed. We also integrate with your IDX website so the agent can see lead browsing behavior — which listings they viewed, saved, and how their search criteria changed over time. All MLS data access follows your board's rules and usage guidelines.
Will agents actually use an AI tool, or will they resist it?
Agent adoption is the most predictable challenge in any real estate AI project, and we design for it. The agents who adopt fastest are the ones who see an immediate time savings on tasks they already hate — qualifying cold internet leads, scheduling showings, and pulling comps. We don't start with tools that touch the relationship-building side of sales (that's where resistance is highest). Instead, we deploy the lead qualification agent first — it handles the initial response to new internet leads within 2 minutes, qualifies them through a natural conversation, and only routes hot leads to the agent's phone. When an agent gets a notification that says 'pre-approved buyer, looking in your farm area, wants to see 3 homes this weekend' instead of a raw Zillow lead, adoption follows.
How does the AI agent handle after-hours lead response?
This is actually the highest-ROI use case for real estate AI agents. Industry data shows that leads contacted within 5 minutes are 100x more likely to convert than leads contacted after 30 minutes — but most leads come in evenings and weekends when agents are off. The AI agent responds instantly 24/7 via text, email, or web chat. It introduces itself, asks qualifying questions (timeline, budget, pre-approval status, areas of interest), shares relevant listings based on their criteria, and if the lead is hot, can book a showing or phone call for the next available time slot on the agent's calendar. The agent wakes up to a qualified lead with context, not a cold callback list.
How do you ensure Fair Housing compliance in AI lead handling?
Fair Housing compliance in AI is non-negotiable and designed into the system architecture. The lead qualification agent never asks about or scores leads based on race, religion, national origin, familial status, disability, sex, or any other protected class. Property matching algorithms recommend based on stated criteria (price, beds, baths, location preference, school district) and never steer buyers toward or away from neighborhoods based on demographic composition. All agent conversations are logged and auditable. We test the system before deployment by running scenarios designed to trigger steering behavior and verify the agent handles them correctly. We also build monitoring dashboards so your compliance team can audit agent interactions at any time.
Real estate AI specialists — not generic chatbot vendors
We build AI agents that understand MLS data structures, real estate conversation patterns, and Fair Housing compliance requirements. You contract with a US LLC (Florida), communicate in your timezone, and get senior AI engineers with genuine real estate technology experience at 40–60% less than US-only consultancies through our LATAM delivery capacity.
Fair Housing compliant by design
Bias testing and compliance guardrails built into agent architecture
MLS integration experience
RESO Web API, RETS, and major MLS systems across US markets
Ready to qualify leads 24/7 without hiring more staff?
Tell us about your lead volume, response time challenges, and where your agents are spending too much time on low-value tasks. We'll map the AI agent opportunity and give you an honest assessment before you commit.